EP3377967A1 - Graph node with automatically adjusting input ports - Google Patents

Graph node with automatically adjusting input ports

Info

Publication number
EP3377967A1
EP3377967A1 EP16802217.6A EP16802217A EP3377967A1 EP 3377967 A1 EP3377967 A1 EP 3377967A1 EP 16802217 A EP16802217 A EP 16802217A EP 3377967 A1 EP3377967 A1 EP 3377967A1
Authority
EP
European Patent Office
Prior art keywords
input ports
graph node
graph
act
input
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP16802217.6A
Other languages
German (de)
English (en)
French (fr)
Inventor
Peter Morgan
Harminder Singh
Damon Robert Hachmeister
Anthony Christopher Karloff
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Microsoft Technology Licensing LLC
Original Assignee
Microsoft Technology Licensing LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Microsoft Technology Licensing LLC filed Critical Microsoft Technology Licensing LLC
Publication of EP3377967A1 publication Critical patent/EP3377967A1/en
Ceased legal-status Critical Current

Links

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing data switching networks
    • H04L43/04Processing captured monitoring data, e.g. for logfile generation
    • H04L43/045Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00Arrangements for software engineering
    • G06F8/30Creation or generation of source code
    • G06F8/34Graphical or visual programming
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0484Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
    • G06F3/04847Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/20Drawing from basic elements, e.g. lines or circles
    • G06T11/206Drawing of charts or graphs
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general
    • G06T2200/24Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]

Definitions

  • Nodal graphs are one mechanism that visualizes the process in a much more intuitive way for a user. Furthermore, rather than simply visualization, the building of nodal graphs actually constructs the corresponding software. Nodal graphs are constructed from graph nodes that each represent executable components of the software. Furthermore, input ports of a given graph node may be coupled to upstream graph nodes so as to represent dependency from that upstream data node and/or data flow from that upstream data node. Typically, a user may simply gesture that an output port of an upstream graph node is to be coupled to an input port of a downstream graph node. This would enforce a dependency at runtime if the coupling represented a dependency, or cause data to flow at runtime if the coupling represents a data flow.
  • At least some embodiments described herein relate to a graphical user interface system that visually represents a graph node having multiple input ports, and that automatically adjusts the number of input ports to the graph node as open input ports are connected to upstream graph node(s) and/or as used input ports are disconnected from upstream graph node(s). For instance, upon detecting that a set of one or more input ports has just been connected to one or more upstream graph nodes, the system may automatically add one or more additional input ports to the visual representation of the graph node without explicit user instruction. Alternatively or in addition, upon detecting that a set of one or more of the input ports has just been disconnected from one or more upstream graph nodes, the system may automatically remove the determined one or more input ports from the visual representation of the graph node.
  • the principles described herein provide a mechanism in which the building of a nodal graph is more automated, or at least the user is relieved from having to think about exhausting or consolidating input ports as the user constructs or edits the graph.
  • the user or process may focus on the important tasks involved with construction of graphs. This may prove key as nodal graphs can become quite complicated, and distractions from the core concepts of the nodal graph can result in errors in construction itself.
  • each input port retains a spatial order with respect to the graph node. Such ordering can be important as the logic associated with the graph node may depend on, or have improved functioning when, such order of processing of inputs being preserved.
  • Figure 1 abstractly illustrates a computing system in which some embodiments described herein may be employed, and which has thereon an executable component
  • Figure 2 illustrates an example graphical user interface that includes multiple disconnected graph nodes, each with two input ports and an output port;
  • Figure 3 illustrates an architecture of executable components that may be used in order to present a graph of graph nodes within a graphical user interface such as the graphical user interface of Figure 2;
  • Figure 4 illustrates a flowchart of a method for visually representing a graph node having a plurality of input ports
  • Figure 5 illustrates a flowchart of a method for adding additional input ports to the graph node in response to detecting the usage of input ports of the graph node in accordance with the principles described herein;
  • Figures 6A through 6F illustrate various stages of a graph node in which multiple input ports are added in response to multiple performances of the method of Figure 5;
  • Figure 7 illustrates a flowchart of a method for removing extra input ports from a graph node in response to detecting the disconnection of input ports of the graph node in accordance with the principles described herein;
  • Figures 8A through 8G illustrate various stages of a graph node in which multiple input ports are removed in response to multiple performances of the method of Figure 7.
  • At least some embodiments described herein relate to a graphical user interface system that visually represents a graph node having multiple input ports, and that automatically adjusts the number of input ports to the graph node as open input ports are connected to upstream graph node(s) and/or as used input ports are disconnected from upstream graph node(s). For instance, upon detecting that a set of one or more input ports has just been connected to one or more upstream graph nodes, the system may automatically add one or more additional input ports to the visual representation of the graph node without explicit user instruction. Alternatively or in addition, upon detecting that a set of one or more of the input ports has just been disconnected from one or more upstream graph nodes, the system may automatically remove the determined one or more input ports from the visual representation of the graph node.
  • the principles described herein provide a mechanism in which the building of a nodal graph is more automated, or at least the user is relieved from having to think about exhausting or consolidating input ports as the user constructs or edits the graph. Instead, the user or process may focus on the important tasks involved with construction of graphs. This may prove key as nodal graphs can become quite complicated, and distractions from the core concepts of the nodal graph can result in errors in construction itself. Furthermore, each input port retains a spatial order with respect to the graph node. Such ordering can be important as the logic associated with the graph node may depend on, or have improved functioning when, such order of processing of inputs being preserved. [0018]
  • Computing systems are now increasingly taking a wide variety of forms.
  • Computing systems may, for example, be handheld devices, appliances, laptop computers, desktop computers, mainframes, distributed computing systems, datacenters, or even devices that have not conventionally been considered a computing system, such as wearables (e.g., glasses).
  • the term "computing system” is defined broadly as including any device or system (or combination thereof) that includes at least one physical and tangible processor, and a physical and tangible memory capable of having thereon computer-executable instructions that may be executed by a processor.
  • the memory may take any form and may depend on the nature and form of the computing system.
  • a computing system may be distributed over a network environment and may include multiple constituent computing systems.
  • a computing system 100 typically includes at least one hardware processing unit 102 and memory 104.
  • the memory 104 may be physical system memory, which may be volatile, non-volatile, or some combination of the two.
  • the term "memory” may also be used herein to refer to non-volatile mass storage such as physical storage media. If the computing system is distributed, the processing, memory and/or storage capability may be distributed as well.
  • the computing system 100 also has thereon multiple structures often referred to as an "executable component".
  • the memory 104 of the computing system 100 is illustrated as including executable component 106.
  • executable component is the name for a structure that is well understood to one of ordinary skill in the art in the field of computing as being a structure that can be software, hardware, or a combination thereof.
  • the structure of an executable component may include software objects, routines, methods that may be executed on the computing system, whether such an executable component exists in the heap of a computing system, or whether the executable component exists on computer-readable storage media.
  • the structure of the executable component exists on a computer-readable medium such that, when interpreted by one or more processors of a computing system (e.g., by a processor thread), the computing system is caused to perform a function.
  • Such structure may be computer- readable directly by the processors (as is the case if the executable component were binary).
  • the structure may be structured to be interpretable and/or compiled (whether in a single stage or in multiple stages) so as to generate such binary that is directly interpretable by the processors.
  • executable component is also well understood by one of ordinary skill as including structures that are implemented exclusively or near-exclusively in hardware, such as within a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit. Accordingly, the term “executable component” is a term for a structure that is well understood by those of ordinary skill in the art of computing, whether implemented in software, hardware, or a combination. In this description, the terms “component”, “service”, “engine”, “module” or the like may also be used. As used in this description and in the case, these terms are also intended to be synonymous with the term “executable component", and thus also have a structure that is well understood by those of ordinary skill in the art of computing.
  • FPGA field programmable gate array
  • ASIC application specific integrated circuit
  • processors of the associated computing system that performs the act
  • computer-executable instructions may be embodied on one or more computer- readable media that form a computer program product.
  • An example of such an operation involves the manipulation of data.
  • the computer-executable instructions may be stored in the memory 104 of the computing system 100.
  • Computing system 100 may also contain communication channels 108 that allow the computing system 100 to communicate with other computing systems over, for example, network 110.
  • the computing system 100 may also include a display 112, which may be used to display visual representations (such as graphical user interfaces showing graphs) to a user.
  • Embodiments described herein may comprise or utilize a special purpose or general-purpose computing system including computer hardware, such as, for example, one or more processors and system memory, as discussed in greater detail below.
  • Embodiments described herein also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures.
  • Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computing system.
  • Computer-readable media that store computer-executable instructions are physical storage media.
  • Computer-readable media that carry computer-executable instructions are transmission media.
  • embodiments of the invention can comprise at least two distinctly different kinds of computer-readable media: storage media and transmission media.
  • Computer-readable storage media includes RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other physical and tangible storage medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computing system.
  • a "network” is defined as one or more data links that enable the transport of electronic data between computing systems and/or modules and/or other electronic devices.
  • a network or another communications connection can include a network and/or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computing system. Combinations of the above should also be included within the scope of computer-readable media.
  • program code means in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to storage media (or vice versa).
  • computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface module (e.g., a "NIC"), and then eventually transferred to computing system RAM and/or to less volatile storage media at a computing system.
  • a network interface module e.g., a "NIC”
  • storage media can be included in computing system components that also (or even primarily) utilize transmission media.
  • Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general purpose computing system, special purpose computing system, or special purpose processing device to perform a certain function or group of functions. Alternatively or in addition, the computer-executable instructions may configure the computing system to perform a certain function or group of functions.
  • the computer executable instructions may be, for example, binaries or even instructions that undergo some translation (such as compilation) before direct execution by the processors, such as intermediate format instructions such as assembly language, or even source code.
  • the invention may be practiced in network computing environments with many types of computing system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, pagers, routers, switches, datacenters, wearables (such as glasses) and the like.
  • the invention may also be practiced in distributed system environments where local and remote computing systems, which are linked (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links) through a network, both perform tasks.
  • program modules may be located in both local and remote memory storage devices.
  • Figure 2 illustrates an example graphical user interface 200 that includes graph nodes 201, 202 and 203.
  • the graphical user interface 200 may be displayed on, for instance, the display 112 of the computing system 100 of Figure 1.
  • ellipses 204 represents flexibility in the number of graph nodes that can be represented within the graphically user interface. There may be from as few as one graph node in a trivial case, to enumerable numbers of graph nodes within any graph represented in the graphical user interface 200.
  • each graph node has one or more input ports and one or more output ports.
  • the author designates connections between one or more output ports of one or more upstream graph nodes and one or more input ports of one or more downstream graph nodes. Those connections enforce dependencies in the execution of the code corresponding to the graph nodes and/or represent the flow of data from upstream to downstream graph nodes.
  • an author may use the graphical user interface 200 to select appropriate graph nodes with appropriate code, and strategically establish connections between those graph nodes to thereby construct complex software having various contributing executable components.
  • the graph node 201 is illustrated as including two input ports 211 and 212 and an output port 213.
  • graph node 202 is illustrated as including two input ports 221 and 222 and output port 223.
  • graph node 203 is illustrated as include two input ports 231 and 232 and output port 233.
  • the principles described herein do not depend on a default starting number of input ports and output ports.
  • the author may also select input ports to see metadata (e.g., an identification) regarding the data flow into that port, or may select output ports to see metadata (e.g., an identification) of the data flow out of that port. If the connection represents a dependency, metadata regarding that dependency might also be viewed by selecting an appropriate input port or output port.
  • new input ports may be automatically added to a graph node as the available input ports to use for connections approaches depletion or becomes depleted (e.g., due to connection of input ports with the output ports of upstream graph node(s)).
  • extra input ports are also automatically removed from a graph node as extra input ports become available (e.g., due to disconnection of input ports from upstream graph node(s)).
  • the number of input ports adjusts automatically without the user having to pay attention to the precise number of input ports.
  • Figure 3 illustrates an architecture 300 of executable components that may be used in order to present a graph of graph nodes within a graphical user interface.
  • the architecture 300 may be used to present the graphical user interface 200 of Figure 2.
  • the architecture 300 includes a graph node visualization component 301 that visualizes graph nodes within a graphical user interface 310 (e.g., which is an example of the graphical user interface 200). There may, but need not, be one graph node visualization module 301 for rendering each graph node within that graph that is rendered on the graph user interface. The graph node visualization module 301 also displays a number of input ports and output ports associated with each graph node.
  • the architecture 300 also includes a detection component 302.
  • the detection component 302 includes a component 302 A that detects an event (as represented by arrow 331) when a new connection is made between an input port of a graph node and an output port of one or more upstream graph nodes within the graphical user interface 310.
  • the detection component 302 also includes another component 302B that detects an event (as represented by arrow 332) when a disconnection is made between an input port of a graph node and an output port of an upstream graph node in the graphical user interface 310.
  • the architecture 300 also includes a port adjustment component 303.
  • the port adjustment component 303 receives a notification (e.g., as represented by arrow 312) from the component 302B that a disconnection has been made from an input port of a graph node that the port adjustment component 303 serves, the port adjustment component 303 will determine whether one or more extra input ports should be removed from the graph node. If so, the port adjustment component 303 will signal (as represented by arrow 322) the graph node visualization component 301 that is responsible for visualizing that graph node to appropriately remove the extra input port(s) from that graph node. This causes (as represented by arrow 342) the removal of the extra input port(s) from the appropriate graph node in the graphical user interface 310.
  • a notification e.g., as represented by arrow 312
  • the port adjustment component 303 will determine whether one or more extra input ports should be removed from the graph node. If so, the port adjustment component 303 will signal (as represented by arrow 322) the graph node visualization component 301 that is responsible for visualizing that graph node to
  • Each of the graph node visualization component 301, the detection component 302, the component 302 A, the component 302B and the port adjustment component 303 are examples of the executable component 106 of Figure 1.
  • each of such components may have any of the structures described above as associated with an executable component.
  • Figure 4 illustrates a flowchart of a method 400 for visually representing a graph node having a plurality of input ports.
  • the method 400 includes representing the graph node on a display as having a number of input ports (act 401). For instance, this act may be performed by the graph node visualization component 301 of Figure 3.
  • the graph node might be, for instance, the graph node 203 of the graphical user interface 200 of Figure 2.
  • the port adjustment component 303 may respond to two different types of events.
  • One event e.g., event 311 of Figure 3
  • the port adjustment component detects that a set of one or more of the input ports has just been connected to one or more upstream graph nodes.
  • This event, and the response thereto is represented by the method 500 of Figure 5, and includes an example process of graph node manipulation with respect to Figures 6A through 6F.
  • Another event e.g., event 312 of Figure 3
  • the port adjustment component detects that a set of one or more of the input ports has just been disconnected from one or more upstream nodes.
  • This event, and the response thereto is represented by the method 700 of Figure 7, and includes an example process of graph node manipulation with respect to Figures 8A through 8G.
  • the method 500 is initiated upon detecting that a set of one or more input ports has just be connected to one or more upstream graph nodes (act 501). For instance, in Figure 3, the component 302A notifies (as represented by arrow 311) the port adjustment component 303 of this connection. In response, the port adjustment component 303 applies its automated logic to determine whether or not an additional one or more input ports is to be added to the graph node (decision block 502). If not ("No" in decision block 502), then no action need be taken in response to the detection (act 503).
  • the port adjustment component determines to respond to the detection (act 501) by adding one or more input ports to the graph node ("Yes" in decision block 502), the port adjustment component causes the one or more additional input ports to be added to the graph node (act 503).
  • the port adjustment component 303 may signal (as represented by arrow 321) the graph node visualization module 301 to thereby cause (as represented by arrow 341) the graph node visualization module 301 to visualize the additional input ports on the graph node within the graphical user interface 310.
  • the user used one or more of the input ports, and the graph node automatically added more input ports for potential use by the user. Accordingly, at least one input port is made available no matter how many input ports already exist and are in use. The user thus does not need to worry about creating input ports, or providing guidance as to how many input ports are needed.
  • Figure 6A through 6F illustrates a graph node in several incremental stages in which input ports are automatically added.
  • the graph node has a default minimum number of input ports of two input ports, and a default maximum number of input ports at six.
  • the minimum and maximum number may be configurable and perhaps in some cases there may be no maximum at all.
  • the illustrated example illustrates only a single kind of input port.
  • the determination of whether or not to add input port(s) to the graph node may be made on a per input port type basis.
  • one input port type might receive string data, and another input port type might receive integers.
  • the input port might have some visualization (such as color, shape, size, and so forth) so that the user can match up input ports of the graph node with appropriate output ports of potential upstream graph nodes.
  • the connection of a particular type of input port with an upstream graph node may have no effect whatsoever on whether or not input ports of any other type should be added.
  • Strl and str2 might have completely different meanings, and each can be expanded to accept a variable number of input ports (but the incoming data to the module will be handled differently between the two sets of inputs).
  • the graph node state of this example manipulation first begins in the state of Figure 6A. In this state, there is an upstream graph node 601 and a downstream graph node 602, and an input port 621 of the graph node 602 has been connected to the output port 611 of the upstream graph node 601 as represented by connection 641. There is one further available input port 622 on the graph node 602. In this example, the connection
  • the upstream graph node 601 provides data in the form of adult census income binary data.
  • the downstream graph node 602 takes in such data and cleans missing data.
  • the exact function of the graph nodes 601 and 602 is not important to the broader principles describe herein, and is merely provided as an example.
  • FIG. 6B the user has established a connection 642 between the output port 611 of the upstream graph node 601 and the previously available input port 622. Without any further adjustment in the number of input ports of the particular graph node 602, this would result in complete exhaustive use of all of the input ports of the graph node 602, with no remaining available input ports available for other connections to upstream graph nodes. However, in accordance with the principles described herein, a further input port 623 has been automatically added to the particular graph node 602. This resulted from one run of the method 500 of Figure 5, which is initiated each time a connection is made from an input port of the particular graph node to an upstream graph node.
  • connection 642 when the connection 642 was first made, this triggered the event 501 of Figure 5, causing the method 500 to be performed.
  • the port adjustment component for the graph node 602 would have then determined whether to add one or more additional input port(s) to the graph node 602 (decision block 602). In the example of Figures 6A through 6F, this determination is based on whether the last available input port has just been connected to an upstream graph node. This is true at the point when the connection
  • the determination (decision block 502) of whether to add input port(s) to the graph node is based on the determination of whether or not the last available input port has just been used by connection to an upstream graph node. However, this need not be the case.
  • the determination (decision block 502) may be that additional input port(s) is/are to be added based on a number of available input ports dropping to a particular threshold due to connections having just been connected to the one or more upstream graph nodes.
  • the particular threshold is that there are no available input ports left - all of them have been used up, as a result of the connection(s) just made.
  • the particular threshold may be that there is but a single (or any number of) available input port left as a result of the connection just made, or that there is but another number of input ports.
  • the particular threshold may even be configurable, and perhaps also may be dependent on the type of input port (e.g., the purpose of the input port). For instance, perhaps input ports of types that are less frequently used have a threshold of zero (all input ports are used before another is added), whereas input ports of types that are more frequently used have a higher threshold to keep well ahead of things as connections are made.
  • FIG. 5 Another variation is in the number of input port(s) that are added (in act 504) when it is determined that additional input port(s) are to be added ("Yes" in decision block 502).
  • the number again may likewise be configurable and/or depend on the input port type. For instance, if it is anticipated that input ports of a particular type are likely to be used commonly in the future, more input ports may be added again to keep ahead of the curve.
  • connection 644 this time between the output port 611 of the upstream graph node 602 and the input port 624. Because all available input ports of the graph node are now used ("Yes" in decision block 502), the input port 625 is added automatically (act 504).
  • the user forms connection 645 between the output port 611 of the upstream graph node 602 and the input port 625, resulting in the input port 626 being automatically added. All the while, the user always has an input port to use without expressly creating it.
  • connection 546 between the output port 611 of the upstream graph node 602 and the input port 626 (act 501). This results in the method 500 being kicked off yet again. However, this time, because the number of input ports has already reached the maximum in this example, it is determined that no further input ports are to be added ("No" in decision block 502). Thus, no further input ports are added (act 503).
  • Figure 7 illustrates a flowchart of a method 700 for removing input ports when connections are disconnected.
  • the method 700 is initiated upon detecting that a set of one or more input ports has just be disconnected from one or more upstream graph nodes (act 701).
  • the component 302B notifies (as represented by arrow 312) the port adjustment component 303 of this disconnection.
  • the port adjustment component 303 applies its automated logic to determine whether or not to remove one or more input ports from the graph node (decision block 702). If not ("No" in decision block 702), then no action need be taken in response to the detection (act 703).
  • the port adjustment component determines to respond to the detection (act 701) by removing one or more input ports from the graph node ("Yes" in decision block 702), the port adjustment component causes the one or more input ports to be removed from the graph node (act 704).
  • the port adjustment component 303 may signal (as represented by arrow 322) the graph node visualization module 301 to thereby cause the graph node visualization module 301 to remove visualizations of the input ports from the graph node.
  • the user is presented with a clean graph node that does not have an excessive number of distracting unused input ports that deemphasize the importance of the input ports that are actually in use.
  • Figure 8A through 8G illustrates a graph node in several incremental stages in which input ports are automatically removed.
  • Figure 8A illustrates the initial stage and is the same as the final stage of the sequence of Figure 6 A through 6F. Accordingly, the stages of Figures 8 A through 8G can be viewed as continuing the example of Figures 6A through 6F.
  • like elements of Figures 8A through 8G share the same numbering as the corresponding elements of Figures 6 A through 6F.
  • the method 700 may be performed independently for each kind of input port type.
  • the disconnection of a particular type of input port from an upstream graph node may have no effect whatsoever on whether or not input ports of any other type are to be removed.
  • connection 646 for elimination, which thereby removes the connection 646 as illustrated in Figure 8C.
  • input port 626 becomes available, and represents an example of the event 312 of Figure 3.
  • This also represents an example of the detection of act 701 of Figure 7, thereby triggering the input port adjustment component executing the method 700 of Figure 7.
  • the determination (decision block 702) of whether to remove input port(s) from the graph node is based on the determination of whether or not there would be more than two available input ports due to the disconnection (of act 701) of the input port(s) from upstream graph node(s). However, this need not be the case.
  • the determination (decision block 702) may be that input port(s) is/are to be removed being based on there being a particular number of available input ports due to the disconnection(s). In this example of Figures 8A through 8G, the particular number is that there are two available input ports due to the disconnection, resulting in one input port being removed.
  • the particular threshold may be any other number, but is preferably such that after performing act 704, there is at least one input port still available in case the user decides to start connecting input ports again.
  • the particular threshold may even be configurable, and perhaps also may be dependent on the type of input port.
  • FIG. 8A Another variation is in the number of input port(s) that are removed (in act 704) when it is determined that the extra input port(s) are to be removed ("Yes" in decision block 702).
  • the number again may likewise be configurable and/or depend on the input port type. Regardless of what the number removed is to be, it is preferably such that after performing act 704, there is at least one input port still available in case the user decides to start connecting input ports again.
  • the port adjustment component 303 causes compacting of the connections such that the available input ports are consolidated contiguously at one end of the graph node, and such that the used input ports are consolidated contiguously at the other end of the graph node. Accordingly, the port adjustment component 303 may remove connection 645 and reestablish connection 644. More generally stated, the port adjustment component causes the functionality of the input ports 624 and 625 to be reversed.
  • compacting results from disconnecting or connecting input ports may also consider the input port type. For instance, if there were two input port types, those input ports of the first type might be compacted towards the left side of the graph node, and those input ports of the second type might be compacted towards another spatial reference point (such as a point in the middle of the graph node, or perhaps the right edge of the graph node).
  • Figure 8F results if the user were to select to disconnect connection 644 of Figure 8E.
  • the connection 644 is removed, resulting in two extra input ports 624 and 625. Accordingly, one extra input port 625 is removed.
  • Figure 8G results if the user were to select to disconnect connection 643 of Figure 8F.
  • the connection 643 is removed, resulting in two extra input ports 623 and 624. Accordingly, one extra input port 624 is removed.
  • Figure 8G results if the user were to disconnect connection 643 in Figure 8G.
  • the connection 643 is removed, resulting in two extra input ports 623 and 624. Accordingly, one extra input port 624 is removed.
  • Figure 8G results if the user were to disconnect connection 643 in Figure 8G.
  • Connection 642 would be removed resulting in two extra input ports 622 and 623.
  • the input port 623 would thus be removed.
  • the principles described herein allow for automated addition of input ports as needed, and/or the automated cleanup of extra input ports.
  • the use is provided with all of the input ports needed, as needed, when formulating the graph node, and is prevented from being distracted by surplus input ports.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Human Computer Interaction (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • User Interface Of Digital Computer (AREA)
EP16802217.6A 2015-11-17 2016-11-14 Graph node with automatically adjusting input ports Ceased EP3377967A1 (en)

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US14/944,005 US10212056B2 (en) 2015-11-17 2015-11-17 Graph node with automatically adjusting input ports
PCT/US2016/061764 WO2017087297A1 (en) 2015-11-17 2016-11-14 Graph node with automatically adjusting input ports

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US10212056B2 (en) * 2015-11-17 2019-02-19 Microsoft Technology Licensing, Llc Graph node with automatically adjusting input ports
CN116266111A (zh) * 2021-12-17 2023-06-20 北京字跳网络技术有限公司 一种群组节点编辑方法及装置

Family Cites Families (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0855019A (ja) * 1994-08-10 1996-02-27 Hitachi Ltd 視覚的プログラミング方法
US5999729A (en) * 1997-03-06 1999-12-07 Continuum Software, Inc. System and method for developing computer programs for execution on parallel processing systems
US6331864B1 (en) 1997-09-23 2001-12-18 Onadime, Inc. Real-time multimedia visual programming system
JP4011701B2 (ja) * 1997-12-05 2007-11-21 キヤノン株式会社 検索装置及び制御方法
US20030130821A1 (en) * 2001-11-09 2003-07-10 Sun Microsystems, Inc. Method, system, and program for rendering a visualization of network devices
US20080040181A1 (en) * 2006-04-07 2008-02-14 The University Of Utah Research Foundation Managing provenance for an evolutionary workflow process in a collaborative environment
US7912964B2 (en) * 2007-06-08 2011-03-22 Apple Inc. Method and apparatus for refactoring a graph in a graphical programming language
EP2633398B1 (en) * 2010-10-25 2020-05-27 Ab Initio Technology LLC Managing data set objects in a dataflow graph that represents a computer program
US20120221998A1 (en) 2011-02-24 2012-08-30 Active Endpoints, Inc. Screenflow designer with automatically changing view
US8601481B2 (en) * 2011-03-02 2013-12-03 International Business Machines Corporation Workflow validation and execution
US20130066936A1 (en) 2011-04-14 2013-03-14 Ram Krishnan Proximal Adaptive Collapsed Cloud Systems
KR20130094932A (ko) * 2012-02-17 2013-08-27 (주)에프엑스기어 포트-에지 시스템을 이용한 노드 그래프 생성 방법
US8676857B1 (en) * 2012-08-23 2014-03-18 International Business Machines Corporation Context-based search for a data store related to a graph node
US9646262B2 (en) 2013-06-17 2017-05-09 Purepredictive, Inc. Data intelligence using machine learning
US9984482B2 (en) * 2013-08-23 2018-05-29 Ab Initio Technology Llc Graphical user interface having enhanced tool for connecting components
US10212056B2 (en) * 2015-11-17 2019-02-19 Microsoft Technology Licensing, Llc Graph node with automatically adjusting input ports

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US10764164B2 (en) 2020-09-01
CN108351767B (zh) 2022-06-10
US20170141976A1 (en) 2017-05-18
CN108351767A (zh) 2018-07-31
US20190182131A1 (en) 2019-06-13
US10212056B2 (en) 2019-02-19
WO2017087297A1 (en) 2017-05-26

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